Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations1143
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.2 KiB
Average record size in memory104.1 B

Variable types

Numeric13

Alerts

citric acid is highly overall correlated with fixed acidity and 2 other fieldsHigh correlation
density is highly overall correlated with fixed acidityHigh correlation
fixed acidity is highly overall correlated with citric acid and 2 other fieldsHigh correlation
free sulfur dioxide is highly overall correlated with total sulfur dioxideHigh correlation
pH is highly overall correlated with citric acid and 1 other fieldsHigh correlation
total sulfur dioxide is highly overall correlated with free sulfur dioxideHigh correlation
volatile acidity is highly overall correlated with citric acidHigh correlation
Id has unique values Unique
citric acid has 99 (8.7%) zeros Zeros

Reproduction

Analysis started2025-06-18 13:43:36.439619
Analysis finished2025-06-18 13:44:08.494297
Duration32.05 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

fixed acidity
Real number (ℝ)

High correlation 

Distinct91
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3111111
Minimum4.6
Maximum15.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:08.635580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum4.6
5-th percentile6.1
Q17.1
median7.9
Q39.1
95-th percentile11.9
Maximum15.9
Range11.3
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.747595
Coefficient of variation (CV)0.21027213
Kurtosis1.3846135
Mean8.3111111
Median Absolute Deviation (MAD)0.9
Skewness1.04493
Sum9499.6
Variance3.0540883
MonotonicityNot monotonic
2025-06-18T13:44:08.824394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2 43
 
3.8%
7.1 41
 
3.6%
7.8 40
 
3.5%
7 40
 
3.5%
7.5 37
 
3.2%
7.9 35
 
3.1%
7.7 34
 
3.0%
7.6 34
 
3.0%
7.3 32
 
2.8%
7.4 32
 
2.8%
Other values (81) 775
67.8%
ValueCountFrequency (%)
4.6 1
 
0.1%
4.9 1
 
0.1%
5 6
0.5%
5.1 4
0.3%
5.2 5
0.4%
5.3 4
0.3%
5.4 3
 
0.3%
5.6 8
0.7%
5.7 1
 
0.1%
5.8 2
 
0.2%
ValueCountFrequency (%)
15.9 1
0.1%
15.6 2
0.2%
15.5 1
0.1%
15 2
0.2%
14.3 1
0.1%
13.8 1
0.1%
13.7 1
0.1%
13.5 1
0.1%
13.4 1
0.1%
13.3 2
0.2%

volatile acidity
Real number (ℝ)

High correlation 

Distinct135
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.53133858
Minimum0.12
Maximum1.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:08.953147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.12
5-th percentile0.271
Q10.3925
median0.52
Q30.64
95-th percentile0.84
Maximum1.58
Range1.46
Interquartile range (IQR)0.2475

Descriptive statistics

Standard deviation0.17963319
Coefficient of variation (CV)0.3380767
Kurtosis1.3755313
Mean0.53133858
Median Absolute Deviation (MAD)0.12
Skewness0.68154741
Sum607.32
Variance0.032268084
MonotonicityNot monotonic
2025-06-18T13:44:09.212761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 32
 
2.8%
0.5 32
 
2.8%
0.43 31
 
2.7%
0.39 29
 
2.5%
0.58 28
 
2.4%
0.36 26
 
2.3%
0.38 26
 
2.3%
0.49 25
 
2.2%
0.52 25
 
2.2%
0.59 25
 
2.2%
Other values (125) 864
75.6%
ValueCountFrequency (%)
0.12 2
 
0.2%
0.16 1
 
0.1%
0.18 8
0.7%
0.19 1
 
0.1%
0.2 2
 
0.2%
0.21 4
 
0.3%
0.22 5
0.4%
0.23 2
 
0.2%
0.24 12
1.0%
0.25 4
 
0.3%
ValueCountFrequency (%)
1.58 1
 
0.1%
1.33 2
0.2%
1.18 1
 
0.1%
1.09 1
 
0.1%
1.07 1
 
0.1%
1.04 3
0.3%
1.035 1
 
0.1%
1.025 1
 
0.1%
1.02 3
0.3%
1.005 1
 
0.1%

citric acid
Real number (ℝ)

High correlation  Zeros 

Distinct77
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.26836395
Minimum0
Maximum1
Zeros99
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:09.379730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.09
median0.25
Q30.42
95-th percentile0.619
Maximum1
Range1
Interquartile range (IQR)0.33

Descriptive statistics

Standard deviation0.19668585
Coefficient of variation (CV)0.73290712
Kurtosis-0.7146856
Mean0.26836395
Median Absolute Deviation (MAD)0.17
Skewness0.37156078
Sum306.74
Variance0.038685325
MonotonicityNot monotonic
2025-06-18T13:44:09.541048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 99
 
8.7%
0.49 47
 
4.1%
0.24 42
 
3.7%
0.02 35
 
3.1%
0.26 26
 
2.3%
0.01 26
 
2.3%
0.31 24
 
2.1%
0.21 23
 
2.0%
0.03 23
 
2.0%
0.3 22
 
1.9%
Other values (67) 776
67.9%
ValueCountFrequency (%)
0 99
8.7%
0.01 26
 
2.3%
0.02 35
 
3.1%
0.03 23
 
2.0%
0.04 19
 
1.7%
0.05 16
 
1.4%
0.06 17
 
1.5%
0.07 19
 
1.7%
0.08 22
 
1.9%
0.09 19
 
1.7%
ValueCountFrequency (%)
1 1
 
0.1%
0.79 1
 
0.1%
0.76 3
 
0.3%
0.75 1
 
0.1%
0.74 4
0.3%
0.73 3
 
0.3%
0.72 1
 
0.1%
0.69 3
 
0.3%
0.68 8
0.7%
0.67 2
 
0.2%

residual sugar
Real number (ℝ)

Distinct80
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5321522
Minimum0.9
Maximum15.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:09.690075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile1.6
Q11.9
median2.2
Q32.6
95-th percentile5.195
Maximum15.5
Range14.6
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation1.3559175
Coefficient of variation (CV)0.53548023
Kurtosis27.675366
Mean2.5321522
Median Absolute Deviation (MAD)0.3
Skewness4.3610964
Sum2894.25
Variance1.8385122
MonotonicityNot monotonic
2025-06-18T13:44:09.853658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 107
 
9.4%
2.1 103
 
9.0%
1.8 92
 
8.0%
2.2 88
 
7.7%
1.9 80
 
7.0%
2.3 75
 
6.6%
2.4 64
 
5.6%
2.6 61
 
5.3%
1.7 59
 
5.2%
2.5 57
 
5.0%
Other values (70) 357
31.2%
ValueCountFrequency (%)
0.9 1
 
0.1%
1.2 4
 
0.3%
1.3 5
 
0.4%
1.4 25
 
2.2%
1.5 20
 
1.7%
1.6 42
3.7%
1.65 2
 
0.2%
1.7 59
5.2%
1.75 2
 
0.2%
1.8 92
8.0%
ValueCountFrequency (%)
15.5 1
 
0.1%
15.4 1
 
0.1%
13.8 2
0.2%
11 2
0.2%
9 1
 
0.1%
8.8 1
 
0.1%
8.6 1
 
0.1%
8.3 3
0.3%
8.1 1
 
0.1%
7.9 3
0.3%

chlorides
Real number (ℝ)

Distinct131
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.086932633
Minimum0.012
Maximum0.611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:10.000522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.012
5-th percentile0.054
Q10.07
median0.079
Q30.09
95-th percentile0.123
Maximum0.611
Range0.599
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.047267338
Coefficient of variation (CV)0.54372376
Kurtosis47.078324
Mean0.086932633
Median Absolute Deviation (MAD)0.01
Skewness6.0263602
Sum99.364
Variance0.0022342012
MonotonicityNot monotonic
2025-06-18T13:44:10.132766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.08 48
 
4.2%
0.077 41
 
3.6%
0.074 38
 
3.3%
0.084 38
 
3.3%
0.078 36
 
3.1%
0.082 35
 
3.1%
0.075 34
 
3.0%
0.076 33
 
2.9%
0.079 31
 
2.7%
0.07 29
 
2.5%
Other values (121) 780
68.2%
ValueCountFrequency (%)
0.012 2
0.2%
0.034 1
 
0.1%
0.038 2
0.2%
0.039 3
0.3%
0.041 4
0.3%
0.042 2
0.2%
0.043 1
 
0.1%
0.044 4
0.3%
0.045 3
0.3%
0.046 2
0.2%
ValueCountFrequency (%)
0.611 1
 
0.1%
0.61 1
 
0.1%
0.467 1
 
0.1%
0.422 1
 
0.1%
0.415 3
0.3%
0.414 2
0.2%
0.403 1
 
0.1%
0.387 1
 
0.1%
0.358 1
 
0.1%
0.341 1
 
0.1%

free sulfur dioxide
Real number (ℝ)

High correlation 

Distinct53
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.615486
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:10.300741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q17
median13
Q321
95-th percentile35
Maximum68
Range67
Interquartile range (IQR)14

Descriptive statistics

Standard deviation10.250486
Coefficient of variation (CV)0.65643083
Kurtosis1.9321699
Mean15.615486
Median Absolute Deviation (MAD)6
Skewness1.2312612
Sum17848.5
Variance105.07247
MonotonicityNot monotonic
2025-06-18T13:44:10.458868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 99
 
8.7%
5 80
 
7.0%
12 58
 
5.1%
10 52
 
4.5%
15 51
 
4.5%
7 51
 
4.5%
9 48
 
4.2%
16 47
 
4.1%
8 45
 
3.9%
17 40
 
3.5%
Other values (43) 572
50.0%
ValueCountFrequency (%)
1 3
 
0.3%
3 33
 
2.9%
4 31
 
2.7%
5 80
7.0%
6 99
8.7%
7 51
4.5%
8 45
3.9%
9 48
4.2%
10 52
4.5%
11 39
 
3.4%
ValueCountFrequency (%)
68 2
0.2%
66 1
 
0.1%
55 1
 
0.1%
53 1
 
0.1%
52 2
0.2%
51 2
0.2%
48 4
0.3%
46 1
 
0.1%
45 2
0.2%
43 2
0.2%

total sulfur dioxide
Real number (ℝ)

High correlation 

Distinct138
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.914698
Minimum6
Maximum289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:10.613535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile12
Q121
median37
Q361
95-th percentile112
Maximum289
Range283
Interquartile range (IQR)40

Descriptive statistics

Standard deviation32.78213
Coefficient of variation (CV)0.713979
Kurtosis5.0987478
Mean45.914698
Median Absolute Deviation (MAD)18
Skewness1.665766
Sum52480.5
Variance1074.6681
MonotonicityNot monotonic
2025-06-18T13:44:10.784871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 36
 
3.1%
15 28
 
2.4%
14 27
 
2.4%
20 27
 
2.4%
18 26
 
2.3%
24 25
 
2.2%
31 24
 
2.1%
16 24
 
2.1%
19 24
 
2.1%
23 22
 
1.9%
Other values (128) 880
77.0%
ValueCountFrequency (%)
6 1
 
0.1%
7 2
 
0.2%
8 10
 
0.9%
9 13
1.1%
10 17
1.5%
11 13
1.1%
12 21
1.8%
13 19
1.7%
14 27
2.4%
15 28
2.4%
ValueCountFrequency (%)
289 1
0.1%
278 1
0.1%
165 1
0.1%
152 1
0.1%
151 1
0.1%
149 1
0.1%
148 1
0.1%
147 2
0.2%
145 1
0.1%
144 1
0.1%

density
Real number (ℝ)

High correlation 

Distinct388
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.99673041
Minimum0.99007
Maximum1.00369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:10.968715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.99007
5-th percentile0.993602
Q10.99557
median0.99668
Q30.997845
95-th percentile1
Maximum1.00369
Range0.01362
Interquartile range (IQR)0.002275

Descriptive statistics

Standard deviation0.0019250671
Coefficient of variation (CV)0.001931382
Kurtosis0.8881233
Mean0.99673041
Median Absolute Deviation (MAD)0.00114
Skewness0.10239511
Sum1139.2629
Variance3.7058835 × 10-6
MonotonicityNot monotonic
2025-06-18T13:44:11.166036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9976 27
 
2.4%
0.9972 25
 
2.2%
0.9968 22
 
1.9%
0.9994 22
 
1.9%
0.9964 21
 
1.8%
0.9982 20
 
1.7%
0.998 20
 
1.7%
0.9978 18
 
1.6%
0.9962 18
 
1.6%
0.9988 16
 
1.4%
Other values (378) 934
81.7%
ValueCountFrequency (%)
0.99007 1
0.1%
0.9902 1
0.1%
0.99064 2
0.2%
0.99084 1
0.1%
0.9912 1
0.1%
0.99154 1
0.1%
0.99157 1
0.1%
0.9916 2
0.2%
0.99162 1
0.1%
0.9917 1
0.1%
ValueCountFrequency (%)
1.00369 1
0.1%
1.0032 1
0.1%
1.00315 2
0.2%
1.00289 1
0.1%
1.0026 2
0.2%
1.00242 2
0.2%
1.0022 2
0.2%
1.0021 2
0.2%
1.0018 1
0.1%
1.0015 2
0.2%

pH
Real number (ℝ)

High correlation 

Distinct87
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3110149
Minimum2.74
Maximum4.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:11.317815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.74
5-th percentile3.07
Q13.205
median3.31
Q33.4
95-th percentile3.57
Maximum4.01
Range1.27
Interquartile range (IQR)0.195

Descriptive statistics

Standard deviation0.15666406
Coefficient of variation (CV)0.047316024
Kurtosis0.92579081
Mean3.3110149
Median Absolute Deviation (MAD)0.1
Skewness0.22113839
Sum3784.49
Variance0.024543628
MonotonicityNot monotonic
2025-06-18T13:44:11.736431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 41
 
3.6%
3.36 40
 
3.5%
3.38 38
 
3.3%
3.39 37
 
3.2%
3.26 33
 
2.9%
3.28 32
 
2.8%
3.32 32
 
2.8%
3.2 31
 
2.7%
3.35 30
 
2.6%
3.22 30
 
2.6%
Other values (77) 799
69.9%
ValueCountFrequency (%)
2.74 1
 
0.1%
2.86 1
 
0.1%
2.88 2
 
0.2%
2.89 3
0.3%
2.9 1
 
0.1%
2.92 3
0.3%
2.93 2
 
0.2%
2.94 3
0.3%
2.95 1
 
0.1%
2.98 5
0.4%
ValueCountFrequency (%)
4.01 2
0.2%
3.9 2
0.2%
3.78 2
0.2%
3.75 1
 
0.1%
3.74 1
 
0.1%
3.72 2
0.2%
3.71 1
 
0.1%
3.7 1
 
0.1%
3.69 3
0.3%
3.68 4
0.3%

sulphates
Real number (ℝ)

Distinct89
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.65770779
Minimum0.33
Maximum2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:11.904548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.33
5-th percentile0.47
Q10.55
median0.62
Q30.73
95-th percentile0.93
Maximum2
Range1.67
Interquartile range (IQR)0.18

Descriptive statistics

Standard deviation0.17039871
Coefficient of variation (CV)0.25907967
Kurtosis12.017377
Mean0.65770779
Median Absolute Deviation (MAD)0.08
Skewness2.4972661
Sum751.76
Variance0.029035722
MonotonicityNot monotonic
2025-06-18T13:44:12.084389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 53
 
4.6%
0.62 50
 
4.4%
0.56 47
 
4.1%
0.54 46
 
4.0%
0.57 42
 
3.7%
0.58 41
 
3.6%
0.55 40
 
3.5%
0.59 39
 
3.4%
0.53 36
 
3.1%
0.61 36
 
3.1%
Other values (79) 713
62.4%
ValueCountFrequency (%)
0.33 1
 
0.1%
0.39 5
 
0.4%
0.4 4
 
0.3%
0.42 4
 
0.3%
0.43 5
 
0.4%
0.44 13
1.1%
0.45 5
 
0.4%
0.46 11
1.0%
0.47 13
1.1%
0.48 20
1.7%
ValueCountFrequency (%)
2 1
0.1%
1.95 2
0.2%
1.62 1
0.1%
1.61 1
0.1%
1.56 1
0.1%
1.36 2
0.2%
1.34 1
0.1%
1.33 1
0.1%
1.31 1
0.1%
1.26 1
0.1%

alcohol
Real number (ℝ)

Distinct61
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.442111
Minimum8.4
Maximum14.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:12.214350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum8.4
5-th percentile9.2
Q19.5
median10.2
Q311.1
95-th percentile12.5
Maximum14.9
Range6.5
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.0821956
Coefficient of variation (CV)0.10363762
Kurtosis0.22117897
Mean10.442111
Median Absolute Deviation (MAD)0.7
Skewness0.86331323
Sum11935.333
Variance1.1711473
MonotonicityNot monotonic
2025-06-18T13:44:12.430454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.5 92
 
8.0%
9.4 72
 
6.3%
9.8 57
 
5.0%
9.2 50
 
4.4%
10 49
 
4.3%
10.5 48
 
4.2%
9.3 44
 
3.8%
9.6 44
 
3.8%
9.7 42
 
3.7%
11 39
 
3.4%
Other values (51) 606
53.0%
ValueCountFrequency (%)
8.4 2
 
0.2%
8.5 1
 
0.1%
8.7 1
 
0.1%
8.8 2
 
0.2%
9 19
 
1.7%
9.1 17
 
1.5%
9.2 50
4.4%
9.233333333 1
 
0.1%
9.25 1
 
0.1%
9.3 44
3.8%
ValueCountFrequency (%)
14.9 1
 
0.1%
14 6
0.5%
13.6 4
0.3%
13.56666667 1
 
0.1%
13.4 2
 
0.2%
13.3 3
0.3%
13.2 1
 
0.1%
13.1 2
 
0.2%
13 3
0.3%
12.9 7
0.6%

quality
Real number (ℝ)

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6570429
Minimum3
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:12.555205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5
Q15
median6
Q36
95-th percentile7
Maximum8
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.80582425
Coefficient of variation (CV)0.1424462
Kurtosis0.31466394
Mean5.6570429
Median Absolute Deviation (MAD)1
Skewness0.2867917
Sum6466
Variance0.64935272
MonotonicityNot monotonic
2025-06-18T13:44:12.649140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 483
42.3%
6 462
40.4%
7 143
 
12.5%
4 33
 
2.9%
8 16
 
1.4%
3 6
 
0.5%
ValueCountFrequency (%)
3 6
 
0.5%
4 33
 
2.9%
5 483
42.3%
6 462
40.4%
7 143
 
12.5%
8 16
 
1.4%
ValueCountFrequency (%)
8 16
 
1.4%
7 143
 
12.5%
6 462
40.4%
5 483
42.3%
4 33
 
2.9%
3 6
 
0.5%

Id
Real number (ℝ)

Unique 

Distinct1143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean804.96938
Minimum0
Maximum1597
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2025-06-18T13:44:12.776386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile84.1
Q1411
median794
Q31209.5
95-th percentile1518.9
Maximum1597
Range1597
Interquartile range (IQR)798.5

Descriptive statistics

Standard deviation463.99712
Coefficient of variation (CV)0.57641586
Kurtosis-1.2163638
Mean804.96938
Median Absolute Deviation (MAD)402
Skewness-0.010419214
Sum920080
Variance215293.32
MonotonicityStrictly increasing
2025-06-18T13:44:12.922719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1597 1
 
0.1%
0 1
 
0.1%
1 1
 
0.1%
2 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
1575 1
 
0.1%
1573 1
 
0.1%
1572 1
 
0.1%
Other values (1133) 1133
99.1%
ValueCountFrequency (%)
0 1
0.1%
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1597 1
0.1%
1595 1
0.1%
1594 1
0.1%
1593 1
0.1%
1592 1
0.1%
1591 1
0.1%
1590 1
0.1%
1587 1
0.1%
1586 1
0.1%
1584 1
0.1%

Interactions

2025-06-18T13:44:05.927201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:37.624624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:46.840238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:49.516736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:51.010443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.765206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.418168image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.972639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.727545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:59.547265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.043989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:02.865030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.402731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:06.055607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:37.935652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:47.098833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:49.627147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:51.122162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.909598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.547676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:56.081275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.828858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:59.648293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.154116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:02.991035image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.514148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:06.181016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:38.066404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:47.750111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:49.766283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:51.240521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.041830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.666174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:56.192910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.943228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:59.767645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.268529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.088826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.623626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:06.359674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:38.150539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:47.907445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:49.885161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:51.356589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.142829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.792471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:56.308789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:58.094568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:59.879451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.375115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.175311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.745828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:06.508616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:43.965073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:48.187698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.001482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:51.464421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.271884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.910259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:56.433181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:58.188318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.002694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.487584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.275708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.848354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:06.651431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:44.248167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:48.307239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.109708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:51.587137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.394326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.021548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:56.580426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:58.310649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.109635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.609538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.404830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.952321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:06.853591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:44.554022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:48.428921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.236098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:51.753185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.523338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.111068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:56.677392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:58.439993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.215705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.733983image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.551571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:05.107347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:06.986966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:45.256841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:48.583967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.369475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.032000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.630662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.204702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:56.998048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:58.583755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.320262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:01.891378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.638802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:05.220776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:07.121985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:45.511912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:48.719153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.475546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.120658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.766469image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.400207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.119813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:58.773865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.446484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:02.031661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.786376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:05.339407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:07.259458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:45.710410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:48.856642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.565401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.211410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:53.898763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.555777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.239809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:58.913593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.616672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:02.349890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:03.912507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:05.439949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:07.390808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:45.903746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:49.016768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.655468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.334442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.026485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.643741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.378690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:59.146702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.744592image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:02.498338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.044516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:05.586591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:07.516219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:46.223789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:49.194091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.775437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.483642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.191313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.739367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.531188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:59.272993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.856346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:02.602014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.229204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:05.687087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:07.645056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:46.379410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:49.344665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:50.896660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:52.593954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:54.318864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:55.850199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:57.618215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:43:59.399430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:00.938465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:02.747659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:04.323516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-18T13:44:05.815704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-18T13:44:13.057153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Idalcoholchloridescitric aciddensityfixed acidityfree sulfur dioxidepHqualityresidual sugarsulphatestotal sulfur dioxidevolatile acidity
Id1.0000.277-0.188-0.125-0.403-0.2890.0870.1430.084-0.115-0.055-0.109-0.001
alcohol0.2771.000-0.3100.091-0.471-0.086-0.0640.1950.4950.1230.199-0.243-0.223
chlorides-0.188-0.3101.0000.1420.4270.2730.002-0.249-0.1940.2020.0020.1260.153
citric acid-0.1250.0910.1421.0000.3550.654-0.075-0.5450.2230.2100.3410.007-0.601
density-0.403-0.4710.4270.3551.0000.630-0.071-0.317-0.1770.4230.1540.1100.019
fixed acidity-0.289-0.0860.2730.6540.6301.000-0.190-0.7070.1040.2430.194-0.094-0.272
free sulfur dioxide0.087-0.0640.002-0.075-0.071-0.1901.0000.114-0.0590.0510.0280.7940.021
pH0.1430.195-0.249-0.545-0.317-0.7070.1141.000-0.033-0.109-0.063-0.0020.222
quality0.0840.495-0.1940.223-0.1770.104-0.059-0.0331.0000.0310.394-0.195-0.398
residual sugar-0.1150.1230.2020.2100.4230.2430.051-0.1090.0311.0000.0310.1240.013
sulphates-0.0550.1990.0020.3410.1540.1940.028-0.0630.3940.0311.000-0.011-0.344
total sulfur dioxide-0.109-0.2430.1260.0070.110-0.0940.794-0.002-0.1950.124-0.0111.0000.102
volatile acidity-0.001-0.2230.153-0.6010.019-0.2720.0210.222-0.3980.013-0.3440.1021.000

Missing values

2025-06-18T13:44:08.115732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-18T13:44:08.315420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholqualityId
07.40.700.001.90.07611.034.00.99783.510.569.450
17.80.880.002.60.09825.067.00.99683.200.689.851
27.80.760.042.30.09215.054.00.99703.260.659.852
311.20.280.561.90.07517.060.00.99803.160.589.863
47.40.700.001.90.07611.034.00.99783.510.569.454
57.40.660.001.80.07513.040.00.99783.510.569.455
67.90.600.061.60.06915.059.00.99643.300.469.456
77.30.650.001.20.06515.021.00.99463.390.4710.077
87.80.580.022.00.0739.018.00.99683.360.579.578
96.70.580.081.80.09715.065.00.99593.280.549.2510
fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholqualityId
11336.70.3200.442.40.06124.034.00.994843.290.8011.671584
11347.50.3100.412.40.06534.060.00.994923.340.8511.461586
11355.80.6100.111.80.06618.028.00.994833.550.6610.961587
11366.30.5500.151.80.07726.035.00.993143.320.8211.661590
11375.40.7400.091.70.08916.026.00.994023.670.5611.661591
11386.30.5100.132.30.07629.040.00.995743.420.7511.061592
11396.80.6200.081.90.06828.038.00.996513.420.829.561593
11406.20.6000.082.00.09032.044.00.994903.450.5810.551594
11415.90.5500.102.20.06239.051.00.995123.520.7611.261595
11425.90.6450.122.00.07532.044.00.995473.570.7110.251597